I'm not certain what is being asked and I need help on where to start.
Assume a significance level of 5% 1. Everybody seems to disagree about why so many parts have to be fixed or thrown away after they are produced. Some say that it's the temperature of the production process, which needs to be held constant (within a reasonable range). Others claim that it's clearly the density of the product
5. A product manager at Proctor & Gamble seeks to determine whether her company should market a new brand of toothpaste, called Tim's of Massachusetts. If the new brand succeeds, then P&G estimates that it would earn $2,000,000 in NPV. If Tim's fails, then the company expects to lose approximately $800,000 in NPV. If P&G decides
I need help interpreting what is being asked and how to solve problems.
See attachment it is in jpeg format.Please show how you devrived at solutions.
See Jpeg attachments. One attachment is a printout from minitab, the other attachment is the questions.
Regression Models: a) The owner has an 82-year-old building with 5 apartments but no parking spots. The lot is 7500 square feet and the gross building area is 9542 square feet. What sales price is predicted by MODEL I ? b) State why you know that all three models are significant for predicting the sales price. Since this is the case, why would a statistician prefer MODEL III to MODEL II ? c) Fill the missing numbers in the analysis-of-variance table for MODEL III. d) From MODEL II to MODEL III the proportion of explained variation in sales price reduces from 98% to 97.7%. Give precisely the reason you know that this is not a significant reduction in R2. e) Use MODEL III to answer this part. On the average, what does an extra apartment add to the sales price? Give a 95% confidence interval for the marginal contribution of the 'apts' variable.
1. The owner of an apartment building in Eurelia believes that her property tax bill is too high because of an overassessment of the property value by the city tax assessor. The owner has hired an independent real-estate appraiser to investigate the appropriateness of the city assessment. The appraiser used regression analysis
Please see attached there are 3 problems. I have added the instructions for #3
The files attached include results from an experiment aimed at determining whether the training program and/or bonus incentive has an effect on employee tenure. ID: Sequential identification numbers assigned to employees included in the study Training: 1=training given to store manager 0=no training given Bon
Is the educational achievement level of students related to how much the state in which they reside spends on education? In many communities this important question is being asked by taxpayers who are being asked by their school districts to increase the amount of tax revenue spent on education. In this case, you will be asked t
The Rio-River Railroad, headquartered in Santa Fe, New Mexico, is trying to devise a method for allocating fuel costs to individual railroad cars on a particular route between Denver and Santa Fe. The railroad thinks that fuel consumption will increase as more cars are added to the train, but it is uncertain how much cost should
This solution gives detailed explanations along with the answers to five questions regarding a given linear regression model.
A company has purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Is age a factor? Is the length of service as a machine operator important? In order to explore further the factors needed to estimate performance on the new
Please see the attached chart and answer the following questions: 1. Find the missing parts of the output (parts a-g). 2. Determine the standard error of the regression model. 3. Is the relationship between y and x1, holding x2 constant, significantly positive? State the hypothesis to be tested, the decision rule, the
Please answer whether these questions or true, false or uncertain. Explain the answer. 1. In a simple linear regression, the coefficient of determinations is the amount of unexplained variation divided by the total variation. 2. If a simple linear regression model's R(squared) is equal to 0.81; then the same model's r wil
1. The attached spreadsheet details the results of a Cobb-Douglas production function estimation for electricity production. Electricity is produced using heat (fuel), capital, and labor. (a) Write out the complete model. (b) What type of returns to scale does electricity production exhibit? (c) Calculate the marginal produ
The standard error of the estimate can be used to determine a range within which the independent X variables can be predicted with varying degrees of statistical confidence based on the regression coefficients and the value for the Y variable. Why is this statement true or false?
Plants emit gases that trigger the ripening of fruit, attract pollinators, and cue other physiological responses. The hydrocarbons emitted by the potato plant were measured and compared to the plant weight. Weight (x) was measured in grams and hydrocarbon emissions (y) were measured in hundreds of nanograms for 11 plants. Let
I am currently working on a problem that has four parts, and in question 1 and 3 I am doing ok. I completed the scatter plot using excel and also have completed the least squares regression model. the part were I am confused is in parts b and c of question 2 and question 4.
This is an example of the basic repeated measures experiment where the study is a completely randomized design (treatments are randomly assigned to experimental units with no blocking factors), and then 4 measurements are made on each unit over time. The tool used for the analysis was SAS.
In a concept formation study, 12 subjects were randomly assigned to three different experimental conditions and then given four trials in the solution of a problem. For each trial, the number of minutes taken to solve the problem was recorded. The results were as follows: (See the attached file for data table) a) State a
Subject: Multivariate model Details: I need to know how to report the findings from this type of model
Making sense of the data in Excel, in order to predict the two most influential , and the two least influential parameters. The enclosed table shows details from a sample of students. All students had to jump as high as possible, the results were measured in CMs. Out of all the personal details, Genda, Height, weight, B
Cost estimation and using multiple regression: University Hospital has prepared a schedule of estimated overhead costs for its blood test unit for the coming year on the assumption that production will be 80,000 tests for the year. Costs have been classified as fixed or variable, according to the controller's judgment. See a
In my paper, I look at the effect of immigration on marital status among different ethnic groups. I would like to get a clear interpretation of my binary logistic regression findings. Although I am including the full SPSS output (in an excel format), I am particularly interested in the meaning of all exp(b) and Nagelkerke R Squa
A used-car dealer randomly selects 100 three-year old Holden Barinas that were sold at auction during the past month. Each car was in top condition and was equipped with automatic transmission, AM/FM cassette tape player, and air conditioning. The dealer recorded the price and the number of km on the odometer. These data are
Compute regression equation, predict grade level, calculate standard error of estimate, and calculate coefficient of determination and non-determination.
The following is a list of grade levels and ages for 15 students: Age Grade 16 10 15 9 15 10 14 8 12 6 11 5 11 6 10 4 9
Lenny's, a national restaurant chain, conducted a study of the factors affecting demand (sales). The following variables were defined and measured for a random sample of 30 of its restaurants. Y = Annual restaurant sales ($000) X1 = Disposable personal income per capita of residents within 5 miles radius X2 = License to se
A) Compute the regression line to explain "water consumption" in terms of "temperature". B) Test, at the alpha= 0.01 level of significance, whether temperature is a significant predictor of water consumption. C) Compute the coefficient of determination of the regression model. D) Find a 99% confidence interval for water consumption on a particular day when the temperature is 28ºC.
An analyst would like to predict water consumption in a city based on daily temperature. She has gathered the following data for a random sample of n= 7 days. Temperature ( C) 40 5 25 15 10 30 35 Water Consumption(million gallons) 225 25 150 100 75 125 175 Using the following sums and sums of squares and cross-products
I need to do the following: Summarize my finding, ensure that all graphs are plotted (please let me know what other graphs need to be included. I need to forecast using two methods. I need to know what columss I should forecast? Are they the original columns given (year, population, dollar, rate)?
Question: Find the forecast of the quaterly earnings per share for Price Club for each quarter by using the naà¯ve approach. See above mentioned forecast values. SECOND PART OF THE QUESTION: The forecast for first-quarter 1994 is the value for fourth quarter 1993,.57. HOW DO I FIND THE ACTUAL FORECAST? I can use cumu
1. If the expected value of Y for the ith observation in a regression model is 35, how could it be that the observed value is 33? 2. In a study of the determination of prices of final output at factor cost in the United Kingdom, the following results were obtained on the basis of annual data for the period 1951-1969: PFt